Course unit code:

A422U4_4B

Course unit title:

Introduction to machine learning

Mode of delivery, planned learning activities and teaching methods:

seminar – 2 hours weekly (on-site method)

Credits allocated:

2

Recommended semester:

Process Control – bachelor (full-time, attendance method), 6. semester

Level of study:

1.

Prerequisites for registration:

none

Assesment methods:

 

Learning outcomes of the course unit:

By completing this course, the student acquired basic knowledge about methods of machine learning. The student also acquired practical skills in data analysis and graphical interpretation using the Python programming language. By completing the course, the student is competent in the design of advanced regression and classification models of different datasets.

Course contents:

Recommended or required reading:

Recommended:

• Guido, S.: Introduction to Machine Learning with Python, O'Reilly Media, Inc, USA, 2016, ISBN: 9781449369415
• Chollet, F.: Deep Learning with Python, Manning Publications, 2017, ISBN: 1617294438
• McKinney, W.: Python for Data Analysis, 2nd edition, O'Reilly Media, Inc, USA, 2017, ISBN: 9781491957660

Language of instruction:

Slovak, English

Name of lecturer(s):

K. Kiš (2023/2024 – Winter)
K. Kiš (2021/2022 – Winter)

Course supervisor:

doc. Ing. MSc. Martin Klaučo, PhD.

Last modification:

15. 7. 2021

AIS: 2021/2022